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- W4386932970 abstract "Abstract. A novel dynamic economic model-predictive control strategy is presented that improves wind farm power production and reduces the additional demands of wake steering on yaw actuation when compared to an industry state-of-the-art reference controller. The novel controller takes a distributed approach to yaw control optimisation using a free-vortex wake model. An actuator-disc representation of the wind turbine is employed and adapted to the wind-farm scale by modelling secondary effects of wake steering and connecting individual turbines through a directed graph network. The economic model-predictive control problem is solved on a receding horizon using gradient-based optimisation, demonstrating sufficient performance for realising real-time control. The novel controller is tested in a large-eddy simulation environment and compared against a state-of-the-art look-up table approach based on steady-state model optimisation. Under realistic variations in wind direction and wind speed, the novel controller yields additional gains in power production during transients as well as a reduction in yaw actuator usage." @default.
- W4386932970 created "2023-09-22" @default.
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- W4386932970 date "2023-09-21" @default.
- W4386932970 modified "2023-10-16" @default.
- W4386932970 title "Dynamic wind farm flow control using free-vortex wake models" @default.
- W4386932970 doi "https://doi.org/10.5194/wes-2023-119" @default.
- W4386932970 hasPublicationYear "2023" @default.
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